The polymer electrolyte fuel cell (PEFC) is receiving widespread attention as an alternative energy resource for transportation applications. However, this technology is far from meeting transportation cost and durability requirements set by the Department of Energy (DOE) for 2010. This disparity is due in part to limitations of the polymer electrolyte, which is responsible for selective transport of protons. To develop improved membranes, one approach is to explore formulations of novel electrolytes with commercially-available polymers. The goal is to exploit the properties of each species within a single membrane through semi-interpenetrating networks (SIPNs). However, due to the abundance of material combinations and the numerous degrees of freedom in polymer processing, an efficient method of screening must be implemented. In this talk, we present high-throughput screening as an effective method of evaluating SIPN formulations that significantly reduces time and cost of sample screening. Combinatorial libraries are synthesized with gradients that capture multiple chemical and/or processing variables. High-throughput analysis techniques are adapted for library characterization. Water sorption and diffusion are desirable properties for high-throughput screening, since the management of water is essential for PEFC performance, and also directly affects other important membrane parameters such as proton conductivity and mechanical strength. We describe a novel apparatus for high-throughput water uptake screening. Various commercially available resins containing blends of poly(vinylidene fluoride) and poly(hexafluoropropylene) have been selected as “host” matrices into which proprietary polyelectrolytes are blended. The effect of compositional variables and crosslinking on diffusivity of water in these membranes, and in Nafion controls, will be discussed. The effect of membrane conditioning before the transport screening will also be evaluated. Finally, water transport will be compared with profiles of conductivity and mechanical strength to identify the correlations between them.

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